{
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      "source": [
        "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
        "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/earthengine-py-notebooks/tree/master/Array/spectral_unmixing.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Array/spectral_unmixing.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Array/spectral_unmixing.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Install Earth Engine API and geemap\n",
        "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://geemap.org). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n",
        "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Installs geemap package\n",
        "import subprocess\n",
        "\n",
        "try:\n",
        "    import geemap\n",
        "except ImportError:\n",
        "    print('Installing geemap ...')\n",
        "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "import ee\n",
        "import geemap"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Create an interactive map \n",
        "The default basemap is `Google Maps`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/basemaps.py) can be added using the `Map.add_basemap()` function. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map = geemap.Map(center=[40,-100], zoom=4)\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Add Earth Engine Python script "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Add Earth Engine dataset\n",
        "# Array-based spectral unmixing.\n",
        "\n",
        "# Create a mosaic of Landsat 5 images from June through September, 2007.\n",
        "allBandMosaic = ee.ImageCollection('LANDSAT/LT05/C01/T1') \\\n",
        "  .filterDate('2007-06-01', '2007-09-30') \\\n",
        "  .select('B[0-7]') \\\n",
        "  .median()\n",
        "\n",
        "# Create some representative endmembers computed previously by sampling\n",
        "# the Landsat 5 mosaic.\n",
        "urbanEndmember = [88, 42, 48, 38, 86, 115, 59]\n",
        "vegEndmember = [50, 21, 20, 35, 50, 110, 23]\n",
        "waterEndmember = [51, 20, 14, 9, 7, 116, 4]\n",
        "\n",
        "# Compute the 3x7 pseudo inverse.\n",
        "endmembers = ee.Array([urbanEndmember, vegEndmember, waterEndmember])\n",
        "inverse = ee.Image(endmembers.matrixPseudoInverse().transpose())\n",
        "\n",
        "# Convert the bands to a 2D 7x1 array. The toArray() call concatenates\n",
        "# pixels from each band along the default axis 0 into a 1D vector per\n",
        "# pixel, and the toArray(1) call concatenates each band (in this case\n",
        "# just the one band of 1D vectors) along axis 1, forming a 2D array.\n",
        "inputValues = allBandMosaic.toArray().toArray(1)\n",
        "\n",
        "# Matrix multiply the pseudo inverse of the endmembers by the pixels to\n",
        "# get a 3x1 set of endmembers fractions from 0 to 1.\n",
        "unmixed = inverse.matrixMultiply(inputValues)\n",
        "\n",
        "# Create and show a colored image of the endmember fractions. Since we know\n",
        "# the result has size 3x1, project down to 1D vectors at each pixel (since the\n",
        "# second axis is pointless now), and then flatten back to a regular scalar\n",
        "# image.\n",
        "colored = unmixed \\\n",
        "  .arrayProject([0]) \\\n",
        "  .arrayFlatten([['urban', 'veg', 'water']])\n",
        "Map.setCenter(-98.4, 19, 11)\n",
        "\n",
        "# Load a hillshade to use as a backdrop.\n",
        "Map.addLayer(ee.Algorithms.Terrain(ee.Image('CGIAR/SRTM90_V4')).select('hillshade'))\n",
        "Map.addLayer(colored, {'min': 0, 'max': 1},\n",
        "  'Unmixed (red=urban, green=veg, blue=water)')\n"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Display Earth Engine data layers "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    }
  ],
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